In this episode of Signal and Noise, hosts Brian Lamar and Andrew DeCilles talk with Lindsay Zaltman, Chief Executive Officer and Partner at Olson Zaltman, the firm known for creating the widely respected ZMET qualitative insight methodology. Together, they explore how deep psychological structures influence the way people think, feel, and make decisions, and why traditional research methods often miss these hidden drivers.

Lindsay explains how deep metaphors guide human behavior at a subconscious level and how they reveal the emotional stories people use to make sense of the world. He shares how Olson Zaltman uncovers these underlying meanings through imagery, personal narratives, and symbolic thinking. The discussion highlights how these insights help brands uncover motivations that consumers cannot easily verbalize and how they lead to more effective strategies, stronger creative ideas, and clearer paths for innovation.

Key Takeaways:

• Why traditional research struggles to reveal emotional truth

• How ZMET identifies the subconscious patterns that shape behavior

• The role of imagery and storytelling in uncovering hidden needs

• Examples of deep metaphors that changed brand strategy

• Why emotional meaning is the foundation of consumer decision making

• How deep metaphors support creative development and positioning

• The value of psychological depth in a fast-moving and automated world

• What it means to understand the stories behind customer choices

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In this episode of Signal & Noise, hosts Brian Lamar and Andrew DeCilles speak with Ben Cortese, Vice President of Decision Sciences and Innovation at KS&R, to explore how custom AI chatbots are reshaping the way research insights are accessed, shared, and expanded beyond traditional deliverables.

Ben explains how his team is combining qualitative and quantitative research with secure AI systems to build proprietary chatbots that allow clients to interact naturally with their own data. These tools help stakeholders ask new questions, explore nuances, and identify early opportunities without re-fielding studies or relying solely on static reports.

The discussion covers how KS&R structures these models to remain accurate, safe, and aligned with proven research findings. Ben also walks through the technical evolution of the tool, including early failures, the role of system guardrails, the importance of loading structured data, and why transparency and validation matter more than speed or novelty.

Key Takeaways:

• What it means to extend insights beyond traditional deliverables

• How custom chatbots are powered by proprietary qualitative content

• Why guardrails are essential to prevent drift, hallucination, and off-topic responses

• The process of grounding AI output to match known research narratives

• How AI can support ideation, early concept testing, and faster client exploration

• Where AI can accelerate the workflow versus where human judgment remains irreplaceable

• How researchers may evolve into curators, validators, and strategic translators

• The future role of AI in tracking, longitudinal analysis, and blended data environments

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In this episode of Signal & Noise, hosts Brian Lamar and Andrew DeCilles welcome the team from Verisoul, a company redefining fraud detection in market research. The guests include Henry LeGard, Founder and CEO, Joey Maddox, Chief Strategy Officer, and Erinn Taylor, who joins the conversation to explore how Verisoul uses banking-grade technology to detect and eliminate fraud while keeping real respondents in the data set.

Henry and Joey explain how Verisoul’s background in cybersecurity and fintech enabled them to develop invisible fraud-prevention tools that identify bots, VPN spoofers, and fraud rings in real time. The team discusses how their system detects human behavior through device patterns, network signals, and even physics-based methods like latency and impossible travel analysis, all without disrupting survey participants.

Brian and Andrew dive into how legacy fraud detection tools often over-block legitimate respondents, creating bias and frustration. The Verisoul team outlines how their approach balances protection with precision, reducing false positives and improving data integrity across the research industry. They also share insights from Verisoul’s large-scale fraud study that analyzed more than 50 million sessions, revealing global fraud trends and the role of device types in fraud rates.

Key Takeaways:

• How Verisoul applies banking-level fraud detection to market research

• The global scale of organized fraud farms and location spoofing

• The impact of false positives on respondent experience and data quality

• Privacy compliance across global markets

• Insights from Verisoul’s fraud research and data quality report

• The concept of real-time fraud and value scoring

• The growing importance of authenticated AI agents in fraud prevention

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Learn more about Verisoul:

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